Personalized Federated Learning with First Order Model Optimization
Not on the map. Why?
Abstract (arXiv)
While federated learning traditionally aims to train a single global model across decentralized local datasets, one model may not always be ideal for all participating clients. Here we propose an alternative, where each client only federates with other relevant clients to obtain a stronger model per client-specific objectives. To achieve this personalization, rather than computing a single model average with constant weights for the entire federation as in traditional FL, we efficiently calculate optimal weighted model combinations for each client, based on figuring out how much a client can benefit from another's model. We do not assume knowledge of any underlying data distributions or client similarities, and allow each client to optimize for arbitrary target distributions of interest, enabling greater flexibility for personalization. We evaluate and characterize our method on a variety of federated settings, datasets, and degrees of local data heterogeneity. Our method outperforms existing alternatives, while also enabling new features for personalized FL such as transfer outside of local data distributions.
Key facts. Cited by 201 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Dec 2020.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 25; 2022: 43; 2023: 42; 2024: 43; 2025: 27; 2026: 21.
201 papers.
Sort:
By area:
- 2021Model-Contrastive Federated Learningcited by 762
- 2021Personalized Federated Learning using Hypernetworkscited by 210
- 2021Federated Multi-Task Learning under a Mixture of Distributionscited by 189
- 2022FedDC: Federated Learning with Non-IID Data via Local Drift Decoupling and Correctioncited by 181
- 2021FedBABU: Towards Enhanced Representation for Federated Image Classificationcited by 180
- 2023Heterogeneous Federated Learning: State-of-the-art and Research Challengescited by 160
- 2022Federated Learning from Pre-Trained Models: A Contrastive Learning Approachcited by 141
- 2022FedALA: Adaptive Local Aggregation for Personalized Federated Learningcited by 121
- 2021Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learningcited by 111
- 2021Parameterized Knowledge Transfer for Personalized Federated Learningcited by 108
- 2023Personalized Federated Learning with Feature Alignment and Classifier Collaborationcited by 97
- 2021Personalized Federated Learning with Gaussian Processescited by 76
38 more
- 2022DisPFL: Towards Communication-Efficient Personalized Federated Learning via Decentralized Sparse Trainingcited by 74
- 2021Personalized Federated Learning through Local Memorizationcited by 57
- 2021FedLab: A Flexible Federated Learning Frameworkcited by 54
- 2022Personalized Subgraph Federated Learningcited by 54
- 2021Adapt to Adaptation: Learning Personalization for Cross-Silo Federated Learningcited by 53
- 2022FederatedScope: A Flexible Federated Learning Platform for Heterogeneitycited by 53
- 2022Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learningcited by 45
- 2023Improving the Model Consistency of Decentralized Federated Learningcited by 45
- 2022pFL-Bench: A Comprehensive Benchmark for Personalized Federated Learningcited by 44
- 2023Recent Advances on Federated Learning: A Systematic Surveycited by 40
- 2022Test-Time Robust Personalization for Federated Learningcited by 39
- 2023Efficient Personalized Federated Learning via Sparse Model-Adaptationcited by 38
- 2023Eliminating Domain Bias for Federated Learning in Representation Spacecited by 38
- 2023FedCP: Separating Feature Information for Personalized Federated Learning via Conditional Policycited by 36
- 2022Federated Learning of Generative Image Priors for MRI Reconstructioncited by 33
- 2022FedTune: A Deep Dive into Efficient Federated Fine-Tuning with Pre-trained Transformerscited by 33
- 2023Exploring One-shot Semi-supervised Federated Learning with A Pre-trained Diffusion Modelcited by 33
- 2021QuPeD: Quantized Personalization via Distillation with Applications to Federated Learningcited by 32
- 2022RSCFed: Random Sampling Consensus Federated Semi-supervised Learningcited by 32
- 2022A Multi-agent Reinforcement Learning Approach for Efficient Client Selection in Federated Learningcited by 28
- 2022Disentangled Federated Learning for Tackling Attributes Skew via Invariant Aggregation and Diversity Transferringcited by 28
- 2023Privacy and Fairness in Federated Learning: on the Perspective of Trade-offcited by 26
- 2023The Best of Both Worlds: Accurate Global and Personalized Models through Federated Learning with Data-Free Hyper-Knowledge Distillationcited by 25
- 2022Towards Effective Clustered Federated Learning: A Peer-to-peer Framework with Adaptive Neighbor Matchingcited by 24
- 2021Personalized Federated Learning for Heterogeneous Clients with Clustered Knowledge Transfercited by 23
- 2022On the (In)security of Peer-to-Peer Decentralized Machine Learningcited by 23
- 2022Accelerated Federated Learning with Decoupled Adaptive Optimizationcited by 23
- 2023Bold but Cautious: Unlocking the Potential of Personalized Federated Learning through Cautiously Aggressive Collaborationcited by 23
- 2023FedPerfix: Towards Partial Model Personalization of Vision Transformers in Federated Learningcited by 21
- 2022SplitGP: Achieving Both Generalization and Personalization in Federated Learningcited by 20
- 2023Optimizing the Collaboration Structure in Cross-Silo Federated Learningcited by 19
- 2022Federated Learning with Heterogeneous Architectures using Graph HyperNetworkscited by 17
- 2023Confidence-aware Personalized Federated Learning via Variational Expectation Maximizationcited by 17
- 2023Federated Prompt Learning for Weather Foundation Models on Devicescited by 17
- 2022Self-Aware Personalized Federated Learningcited by 16
- 2023Visual Prompt Based Personalized Federated Learningcited by 16
- 2023PFLlib: A Beginner-Friendly and Comprehensive Personalized Federated Learning Library and Benchmarkcited by 16
- 2021On Bridging Generic and Personalized Federated Learning for Image Classificationcited by 15
50 most cited of 201 All 201 (JSON)
- 2026PACE: Propagation-Aware Collaborative Correction for One-Shot Personalized Federated Graph Learning4 Sep 2026
- 2026FlatLand: Personalized Graph Federated Learning via Tailored Lorentz Space21 Aug 2026
- 2026FM2: Unified Federated Foundation Models for Heterogeneous Multimodal Medical Imaging15 Jul 2026
- 2026Collaborative Synthetic Data Generation for Knowledge Transfer in Federated Learning8 Jul 2026
- 2026FedSPC: Shared Parameter Correction for Personalized Federated Learning11 Jun 2026
- 2026Separate Aggregation of Split Network for Personalized Federated Learning26 May 2026
- 2026FedCoE: Bridging Generalization and Personalization via Federated Coordinated Dual-level MoEs20 May 2026
- 2026Learned Neighbor Trust for Collaborative Deployment in Model-Agnostic Decentralized Learning6 May 2026
- 2026Personalized Digital Health Modeling with Adaptive Support Users3 May 2026
- 2026FedOBP: Federated Optimal Brain Personalization through Cloud-Edge Element-wise Decoupling17 Apr 2026
- 2026FedRio: Personalized Federated Social Bot Detection via Cooperative Reinforced Contrastive Adversarial Distillation12 Apr 2026
- 2026Bi-level Heterogeneous Learning for Time Series Foundation Models: A Federated Learning Approach8 Apr 2026
38 more
- 2026SubFLOT: Submodel Extraction for Efficient and Personalized Federated Learning via Optimal Transport8 Apr 2026
- 2026FedDES: Graph-Based Dynamic Ensemble Selection for Personalized Federated Learning30 Mar 2026
- 2026OmniFM: Toward Modality-Robust and Task-Agnostic Federated Learning for Heterogeneous Medical Imaging23 Mar 2026
- 2026FedPDPO: Federated Personalized Direct Preference Optimization for Large Language Model Alignment20 Mar 2026
- 2026Probabilistic Federated Learning on Uncertain and Heterogeneous Data with Model Personalization18 Mar 2026
- 2026Few-for-Many Personalized Federated Learning12 Mar 2026
- 2026Personalized Federated Learning via Gaussian Generative Modeling12 Mar 2026
- 2026Federated Ensemble Learning with Progressive Model Personalization15 Feb 2026
- 2026FedKDX: Federated Learning with Negative Knowledge Distillation for Enhanced Healthcare AI Systems8 Jan 2026
- 2025FedeCouple: Fine-Grained Balancing of Global-Generalization and Local-Adaptability in Federated Learning12 Nov 2025
- 2025Local Performance vs. Out-of-Distribution Generalization: An Empirical Analysis of Personalized Federated Learning in Heterogeneous Data Environments28 Oct 2025
- 2025Sentinel: Dynamic Knowledge Distillation for Personalized Federated Intrusion Detection in Heterogeneous IoT Networks27 Oct 2025
- 2025Locally Optimal Private Sampling: Beyond the Global Minimax10 Oct 2025
- 2025Technical note on Fisher Information for Robust Federated Cross-Validation4 Oct 2025
- 2025FedDAF: Federated Domain Adaptation Using Model Functional Distance15 Sep 2025
- 2025FedKLPR: KL-Guided Pruning-Aware Federated Learning for Person Re-Identification24 Aug 2025
- 2025Deploying Models to Non-participating Clients in Federated Learning without Fine-tuning: A Hypernetwork-based Approach18 Aug 2025
- 2025FedShard: Federated Unlearning with Efficiency Fairness and Performance Fairness13 Aug 2025
- 2025FeDaL: Federated Dataset Learning for General Time Series Foundation Models6 Aug 2025
- 2025Federated Learning in Offline and Online EMG Decoding: A Privacy and Performance Perspective16 Jul 2025
- 2025pFedMMA: Personalized Federated Fine-Tuning with Multi-Modal Adapter for Vision-Language Models7 Jul 2025
- 2025Whom to Trust? Adaptive Collaboration in Personalized Federated Learning30 Jun 2025
- 2025Client Clustering Meets Knowledge Sharing: Enhancing Privacy and Robustness in Personalized Peer-to-Peer Learning25 Jun 2025
- 2025SPIRE: Conditional Personalization for Federated Diffusion Generative Models14 Jun 2025
- 2025pFedSOP : Accelerating Training Of Personalized Federated Learning Using Second-Order Optimization8 Jun 2025
- 2025Lazy But Effective: Collaborative Personalized Federated Learning with Heterogeneous Data5 May 2025
- 2025Incentivizing Inclusive Contributions in Model Sharing Markets5 May 2025
- 2025Privacy Preserving Machine Learning Model Personalization through Federated Personalized Learning3 May 2025
- 2025DP2FL: Dual Prompt Personalized Federated Learning in Foundation Models23 Apr 2025
- 2025Collaborative Learning of On-Device Small Model and Cloud-Based Large Model: Advances and Future Directions17 Apr 2025
- 2025FedEPA: Enhancing Personalization and Modality Alignment in Multimodal Federated Learning16 Apr 2025
- 2025Federated Hierarchical Reinforcement Learning for Adaptive Traffic Signal Control7 Apr 2025
- 2025Extra Clients at No Extra Cost: Overcome Data Heterogeneity in Federated Learning with Filter Decomposition11 Mar 2025
- 2025Capture Global Feature Statistics for One-Shot Federated Learning10 Mar 2025
- 2025Chemical knowledge-informed framework for privacy-aware retrosynthesis learning26 Feb 2025
- 2025Privacy-Preserving Personalized Federated Prompt Learning for Multimodal Large Language Models23 Jan 2025
- 2024Federated Source-free Domain Adaptation for Classification: Weighted Cluster Aggregation for Unlabeled Data18 Dec 2024
- 2024Optimizing Personalized Federated Learning through Adaptive Layer-Wise Learning10 Dec 2024
50 newest of 201 All 201 (JSON)
- 2023Exploring One-shot Semi-supervised Federated Learning with A Pre-trained Diffusion Modelcited by 33
- 2024pFedGPA: Diffusion-based Generative Parameter Aggregation for Personalized Federated Learningcited by 0
- 2025SPIRE: Conditional Personalization for Federated Diffusion Generative Modelscited by 0
- 2025SPIRE: Conditional Personalization for Federated Diffusion Generative Models14 Jun 2025
- 2024pFedGPA: Diffusion-based Generative Parameter Aggregation for Personalized Federated Learning9 Sep 2024
- 2023Exploring One-shot Semi-supervised Federated Learning with A Pre-trained Diffusion Model6 May 2023
- 2025Privacy-Preserving Personalized Federated Prompt Learning for Multimodal Large Language Modelscited by 5
- 2024F3OCUS -- Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristicscited by 4
- 2025pFedMMA: Personalized Federated Fine-Tuning with Multi-Modal Adapter for Vision-Language Modelscited by 3
- 2025pFedMMA: Personalized Federated Fine-Tuning with Multi-Modal Adapter for Vision-Language Models7 Jul 2025
- 2025Privacy-Preserving Personalized Federated Prompt Learning for Multimodal Large Language Models23 Jan 2025
- 2024F3OCUS -- Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics17 Nov 2024
- 2021Model-Contrastive Federated Learningcited by 762
- 2021Personalized Federated Learning using Hypernetworkscited by 210
- 2021Federated Multi-Task Learning under a Mixture of Distributionscited by 189
- 2022FedDC: Federated Learning with Non-IID Data via Local Drift Decoupling and Correctioncited by 181
- 2021FedBABU: Towards Enhanced Representation for Federated Image Classificationcited by 180
- 2023Heterogeneous Federated Learning: State-of-the-art and Research Challengescited by 160
- 2022Federated Learning from Pre-Trained Models: A Contrastive Learning Approachcited by 141
- 2022FedALA: Adaptive Local Aggregation for Personalized Federated Learningcited by 121
- 2021Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learningcited by 111
- 2021Parameterized Knowledge Transfer for Personalized Federated Learningcited by 108
- 2023Personalized Federated Learning with Feature Alignment and Classifier Collaborationcited by 97
- 2021Personalized Federated Learning with Gaussian Processescited by 76
12 most cited of 191 All 191 (JSON)
- 2026PACE: Propagation-Aware Collaborative Correction for One-Shot Personalized Federated Graph Learning4 Sep 2026
- 2026FlatLand: Personalized Graph Federated Learning via Tailored Lorentz Space21 Aug 2026
- 2026Collaborative Synthetic Data Generation for Knowledge Transfer in Federated Learning8 Jul 2026
- 2026FedSPC: Shared Parameter Correction for Personalized Federated Learning11 Jun 2026
- 2026Separate Aggregation of Split Network for Personalized Federated Learning26 May 2026
- 2026Learned Neighbor Trust for Collaborative Deployment in Model-Agnostic Decentralized Learning6 May 2026
- 2026Personalized Digital Health Modeling with Adaptive Support Users3 May 2026
- 2026FedOBP: Federated Optimal Brain Personalization through Cloud-Edge Element-wise Decoupling17 Apr 2026
- 2026FedRio: Personalized Federated Social Bot Detection via Cooperative Reinforced Contrastive Adversarial Distillation12 Apr 2026
- 2026Bi-level Heterogeneous Learning for Time Series Foundation Models: A Federated Learning Approach8 Apr 2026
- 2026SubFLOT: Submodel Extraction for Efficient and Personalized Federated Learning via Optimal Transport8 Apr 2026
- 2026FedDES: Graph-Based Dynamic Ensemble Selection for Personalized Federated Learning30 Mar 2026
12 newest of 191 All 191 (JSON)